Overview

Dataset statistics

Number of variables30
Number of observations19587643
Missing cells17325047
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.8 GiB
Average record size in memory973.1 B

Variable types

Numeric9
Categorical11
DateTime9
Unsupported1

Warnings

videoamp_household_id has a high cardinality: 881661 distinct values High cardinality
tms_id has a high cardinality: 5535 distinct values High cardinality
ad_content_title has a high cardinality: 2204 distinct values High cardinality
series_name has a high cardinality: 2280 distinct values High cardinality
episode_title has a high cardinality: 2626 distinct values High cardinality
network has a high cardinality: 79 distinct values High cardinality
callsign has a high cardinality: 1274 distinct values High cardinality
market_name has a high cardinality: 210 distinct values High cardinality
season_number is highly correlated with episode_numberHigh correlation
episode_number is highly correlated with season_numberHigh correlation
timeshift_name is highly correlated with timeshift_secondsHigh correlation
ad_id is highly correlated with network and 1 other fieldsHigh correlation
session_duration_seconds is highly correlated with program_duration_secondsHigh correlation
timeshift_seconds is highly correlated with timeshift_nameHigh correlation
program_duration_seconds is highly correlated with session_duration_seconds and 2 other fieldsHigh correlation
season_number is highly correlated with network and 1 other fieldsHigh correlation
network is highly correlated with ad_id and 3 other fieldsHigh correlation
media_group is highly correlated with ad_id and 3 other fieldsHigh correlation
media_group is highly correlated with networkHigh correlation
ad_id is highly correlated with networkHigh correlation
network is highly correlated with media_group and 1 other fieldsHigh correlation
ad_content_title has 3089626 (15.8%) missing values Missing
episode_title has 6763657 (34.5%) missing values Missing
season_number has 3089626 (15.8%) missing values Missing
episode_number has 3089626 (15.8%) missing values Missing
full_panel_intab_weekly_weight has 1135274 (5.8%) missing values Missing
videoamp_event_key has unique values Unique
airing_date_utc is an unsupported type, check if it needs cleaning or further analysis Unsupported
season_number has 3544177 (18.1%) zeros Zeros
episode_number has 3632098 (18.5%) zeros Zeros
timeshift_seconds has 13628575 (69.6%) zeros Zeros
east_coast_offset_seconds has 16423654 (83.8%) zeros Zeros

Reproduction

Analysis started2021-08-26 21:31:07.642385
Analysis finished2021-08-26 22:54:30.689287
Duration1 hour, 23 minutes and 23.05 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

videoamp_event_key
Real number (ℝ≥0)

UNIQUE

Distinct19587643
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98031599.73
Minimum6
Maximum200243140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:30.885697image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9785912.9
Q149015580
median98017669
Q3147047606
95-th percentile186302756.4
Maximum200243140
Range200243134
Interquartile range (IQR)98032026

Descriptive statistics

Standard deviation56616646.33
Coefficient of variation (CV)0.5775346571
Kurtosis-1.198638944
Mean98031599.73
Median Absolute Deviation (MAD)49015234
Skewness0.001181276093
Sum1.920207978 × 1015
Variance3.205444642 × 1015
MonotonicityNot monotonic
2021-08-26T22:54:31.103276image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
588624361
 
< 0.1%
97832901
 
< 0.1%
1314283511
 
< 0.1%
1747578881
 
< 0.1%
1370071051
 
< 0.1%
447283231
 
< 0.1%
237711401
 
< 0.1%
1202380851
 
< 0.1%
1621770311
 
< 0.1%
405565521
 
< 0.1%
Other values (19587633)19587633
> 99.9%
ValueCountFrequency (%)
61
< 0.1%
141
< 0.1%
241
< 0.1%
291
< 0.1%
351
< 0.1%
501
< 0.1%
591
< 0.1%
701
< 0.1%
751
< 0.1%
931
< 0.1%
ValueCountFrequency (%)
2002431401
< 0.1%
2002383401
< 0.1%
2002381801
< 0.1%
2002369001
< 0.1%
2002367401
< 0.1%
2002362601
< 0.1%
2002260201
< 0.1%
2002258601
< 0.1%
2002257001
< 0.1%
2002255401
< 0.1%

videoamp_household_id
Categorical

HIGH CARDINALITY

Distinct881661
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size2.2 GiB
d267de3041ff24c584024b2e8f3754e87038b7ef15c3d1bb5d5aaed94f1ccc24
 
670
e7a2f8b72cdbb001ffec170e31ed010c37d7beaef83e74aa5524bb272712200b
 
634
3b8a097674dc6199ee33d17d3787bddc492859d3e9b78646c8843d0747a7e3b7
 
593
92287542743d01f1de30a8f5c7977056530192c8ea8a0105fac93011f6b9af80
 
565
7bef78e89dc506c631bdd030481911a403338110e657dc5cc5bdb196117d5a5a
 
543
Other values (881656)
19584638 

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters1253609152
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108478 ?
Unique (%)0.6%

Sample

1st row004c25ab7f5c7914440b6e9b4574ca804a077af28c9d03b2fe8472c29e3db0e1
2nd row004c25ab7f5c7914440b6e9b4574ca804a077af28c9d03b2fe8472c29e3db0e1
3rd row004c25ab7f5c7914440b6e9b4574ca804a077af28c9d03b2fe8472c29e3db0e1
4th row004c25ab7f5c7914440b6e9b4574ca804a077af28c9d03b2fe8472c29e3db0e1
5th row006bf297c0caed8e12fb5f9bcf3f53dc4a63dde1aaa57a875f5a15dc4c74753f

Common Values

ValueCountFrequency (%)
d267de3041ff24c584024b2e8f3754e87038b7ef15c3d1bb5d5aaed94f1ccc24670
 
< 0.1%
e7a2f8b72cdbb001ffec170e31ed010c37d7beaef83e74aa5524bb272712200b634
 
< 0.1%
3b8a097674dc6199ee33d17d3787bddc492859d3e9b78646c8843d0747a7e3b7593
 
< 0.1%
92287542743d01f1de30a8f5c7977056530192c8ea8a0105fac93011f6b9af80565
 
< 0.1%
7bef78e89dc506c631bdd030481911a403338110e657dc5cc5bdb196117d5a5a543
 
< 0.1%
3d75508b22d5385a51a45acadceb62bca14e05b1a6e37eebbea17d212b4618b8523
 
< 0.1%
b2d8aa7913060601fce1fcf723da8e5434acfde46f1acfb7341a85427667e4c6507
 
< 0.1%
b51309fc62ea919a79391b4a26bfcfeedcfd44f43982b939e874a4e4ea71c082502
 
< 0.1%
0545e3f198c0d56a524c56dbe9edd400de65e93dbc29ae1061879a88b110fecd493
 
< 0.1%
d0cf782adf480552a7ba4fa1098194eead8926044e23dc6a0800ac9fdbb11185482
 
< 0.1%
Other values (881651)19582131
> 99.9%

Length

2021-08-26T22:54:31.647867image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
d267de3041ff24c584024b2e8f3754e87038b7ef15c3d1bb5d5aaed94f1ccc24670
 
< 0.1%
e7a2f8b72cdbb001ffec170e31ed010c37d7beaef83e74aa5524bb272712200b634
 
< 0.1%
3b8a097674dc6199ee33d17d3787bddc492859d3e9b78646c8843d0747a7e3b7593
 
< 0.1%
92287542743d01f1de30a8f5c7977056530192c8ea8a0105fac93011f6b9af80565
 
< 0.1%
7bef78e89dc506c631bdd030481911a403338110e657dc5cc5bdb196117d5a5a543
 
< 0.1%
3d75508b22d5385a51a45acadceb62bca14e05b1a6e37eebbea17d212b4618b8523
 
< 0.1%
b2d8aa7913060601fce1fcf723da8e5434acfde46f1acfb7341a85427667e4c6507
 
< 0.1%
b51309fc62ea919a79391b4a26bfcfeedcfd44f43982b939e874a4e4ea71c082502
 
< 0.1%
0545e3f198c0d56a524c56dbe9edd400de65e93dbc29ae1061879a88b110fecd493
 
< 0.1%
d0cf782adf480552a7ba4fa1098194eead8926044e23dc6a0800ac9fdbb11185482
 
< 0.1%
Other values (881651)19582131
> 99.9%

Most occurring characters

ValueCountFrequency (%)
a78510038
 
6.3%
278438081
 
6.3%
478426048
 
6.3%
d78401508
 
6.3%
978390812
 
6.3%
e78387873
 
6.3%
078361082
 
6.3%
778352502
 
6.3%
178345278
 
6.2%
578343081
 
6.2%
Other values (6)469652849
37.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number783593033
62.5%
Lowercase Letter470016119
37.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
278438081
10.0%
478426048
10.0%
978390812
10.0%
078361082
10.0%
778352502
10.0%
178345278
10.0%
578343081
10.0%
678342408
10.0%
878315604
10.0%
378278137
10.0%
Lowercase Letter
ValueCountFrequency (%)
a78510038
16.7%
d78401508
16.7%
e78387873
16.7%
f78296535
16.7%
c78259720
16.7%
b78160445
16.6%

Most occurring scripts

ValueCountFrequency (%)
Common783593033
62.5%
Latin470016119
37.5%

Most frequent character per script

Common
ValueCountFrequency (%)
278438081
10.0%
478426048
10.0%
978390812
10.0%
078361082
10.0%
778352502
10.0%
178345278
10.0%
578343081
10.0%
678342408
10.0%
878315604
10.0%
378278137
10.0%
Latin
ValueCountFrequency (%)
a78510038
16.7%
d78401508
16.7%
e78387873
16.7%
f78296535
16.7%
c78259720
16.7%
b78160445
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1253609152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a78510038
 
6.3%
278438081
 
6.3%
478426048
 
6.3%
d78401508
 
6.3%
978390812
 
6.3%
e78387873
 
6.3%
078361082
 
6.3%
778352502
 
6.3%
178345278
 
6.2%
578343081
 
6.2%
Other values (6)469652849
37.5%

ad_id
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 GiB
LLTR0095000H
15452628 
LLTR0093000H
3872804 
LLTR0084000H
 
226985
LLTR0099000H
 
35226

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters235051716
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLLTR0093000H
2nd rowLLTR0095000H
3rd rowLLTR0095000H
4th rowLLTR0095000H
5th rowLLTR0095000H

Common Values

ValueCountFrequency (%)
LLTR0095000H15452628
78.9%
LLTR0093000H3872804
 
19.8%
LLTR0084000H226985
 
1.2%
LLTR0099000H35226
 
0.2%

Length

2021-08-26T22:54:31.992916image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-08-26T22:54:32.103079image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
lltr0095000h15452628
78.9%
lltr0093000h3872804
 
19.8%
lltr0084000h226985
 
1.2%
lltr0099000h35226
 
0.2%

Most occurring characters

ValueCountFrequency (%)
097938215
41.7%
L39175286
 
16.7%
T19587643
 
8.3%
R19587643
 
8.3%
H19587643
 
8.3%
919395884
 
8.3%
515452628
 
6.6%
33872804
 
1.6%
8226985
 
0.1%
4226985
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number137113501
58.3%
Uppercase Letter97938215
41.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
097938215
71.4%
919395884
 
14.1%
515452628
 
11.3%
33872804
 
2.8%
8226985
 
0.2%
4226985
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
L39175286
40.0%
T19587643
20.0%
R19587643
20.0%
H19587643
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common137113501
58.3%
Latin97938215
41.7%

Most frequent character per script

Common
ValueCountFrequency (%)
097938215
71.4%
919395884
 
14.1%
515452628
 
11.3%
33872804
 
2.8%
8226985
 
0.2%
4226985
 
0.2%
Latin
ValueCountFrequency (%)
L39175286
40.0%
T19587643
20.0%
R19587643
20.0%
H19587643
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII235051716
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
097938215
41.7%
L39175286
 
16.7%
T19587643
 
8.3%
R19587643
 
8.3%
H19587643
 
8.3%
919395884
 
8.3%
515452628
 
6.6%
33872804
 
1.6%
8226985
 
0.1%
4226985
 
0.1%
Distinct14481
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:20:40
Maximum2021-03-22 00:26:10
2021-08-26T22:54:32.254246image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:32.449283image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct14601
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:21:42
Maximum2021-03-22 00:27:11
2021-08-26T22:54:32.656191image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:32.851272image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

ad_duration_seconds
Real number (ℝ≥0)

Distinct62
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.64945486
Minimum4
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:33.053561image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q160
median60
Q361
95-th percentile62
Maximum121
Range117
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.46449462
Coefficient of variation (CV)0.3012746359
Kurtosis4.794630049
Mean54.64945486
Median Absolute Deviation (MAD)1
Skewness-2.568362935
Sum1070454012
Variance271.079583
MonotonicityNot monotonic
2021-08-26T22:54:33.266040image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
606600928
33.7%
615103672
26.1%
623187452
16.3%
591588640
 
8.1%
41170472
 
6.0%
57244137
 
1.2%
5214837
 
1.1%
58193652
 
1.0%
53180324
 
0.9%
21136401
 
0.7%
Other values (52)967128
 
4.9%
ValueCountFrequency (%)
41170472
6.0%
5214837
 
1.1%
659154
 
0.3%
7132475
 
0.7%
851957
 
0.3%
957333
 
0.3%
107152
 
< 0.1%
1111384
 
0.1%
1253619
 
0.3%
1311147
 
0.1%
ValueCountFrequency (%)
12160
 
< 0.1%
120132
 
< 0.1%
9633
 
< 0.1%
674569
 
< 0.1%
65475
 
< 0.1%
623187452
16.3%
615103672
26.1%
606600928
33.7%
591588640
 
8.1%
58193652
 
1.0%

tms_id
Categorical

HIGH CARDINALITY

Distinct5535
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 GiB
EP000031282865
 
359053
EP035115960001
 
143541
EP000031282860
 
86058
EP000031282862
 
83705
SH003248290000
 
76715
Other values (5530)
18838571 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters274227002
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowEP026844840948
2nd rowEP000000351549
3rd rowEP000000351549
4th rowEP015057882387
5th rowMV015471150000

Common Values

ValueCountFrequency (%)
EP000031282865359053
 
1.8%
EP035115960001143541
 
0.7%
EP00003128286086058
 
0.4%
EP00003128286283705
 
0.4%
SH00324829000076715
 
0.4%
EP00500080051675072
 
0.4%
EP00003128283774439
 
0.4%
SH00019131000071658
 
0.4%
SH00877699000069467
 
0.4%
SH03774932000066495
 
0.3%
Other values (5525)18481440
94.4%

Length

2021-08-26T22:54:33.693216image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ep000031282865359053
 
1.8%
ep035115960001143541
 
0.7%
ep00003128286086058
 
0.4%
ep00003128286283705
 
0.4%
sh00324829000076715
 
0.4%
ep00500080051675072
 
0.4%
ep00003128283774439
 
0.4%
sh00019131000071658
 
0.4%
sh00877699000069467
 
0.4%
sh03774932000066495
 
0.3%
Other values (5525)18481440
94.4%

Most occurring characters

ValueCountFrequency (%)
073001403
26.6%
127193829
 
9.9%
221909194
 
8.0%
320297662
 
7.4%
519140675
 
7.0%
E16846538
 
6.1%
P16846538
 
6.1%
815885906
 
5.8%
415395780
 
5.6%
915050241
 
5.5%
Other values (6)32659236
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number235051716
85.7%
Uppercase Letter39175286
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
073001403
31.1%
127193829
 
11.6%
221909194
 
9.3%
320297662
 
8.6%
519140675
 
8.1%
815885906
 
6.8%
415395780
 
6.5%
915050241
 
6.4%
614362231
 
6.1%
712814795
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
E16846538
43.0%
P16846538
43.0%
S1719460
 
4.4%
H1719460
 
4.4%
M1021645
 
2.6%
V1021645
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common235051716
85.7%
Latin39175286
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
073001403
31.1%
127193829
 
11.6%
221909194
 
9.3%
320297662
 
8.6%
519140675
 
8.1%
815885906
 
6.8%
415395780
 
6.5%
915050241
 
6.4%
614362231
 
6.1%
712814795
 
5.5%
Latin
ValueCountFrequency (%)
E16846538
43.0%
P16846538
43.0%
S1719460
 
4.4%
H1719460
 
4.4%
M1021645
 
2.6%
V1021645
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII274227002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
073001403
26.6%
127193829
 
9.9%
221909194
 
8.0%
320297662
 
7.4%
519140675
 
7.0%
E16846538
 
6.1%
P16846538
 
6.1%
815885906
 
5.8%
415395780
 
5.6%
915050241
 
5.5%
Other values (6)32659236
11.9%

ad_content_title
Categorical

HIGH CARDINALITY
MISSING

Distinct2204
Distinct (%)< 0.1%
Missing3089626
Missing (%)15.8%
Memory size1.3 GiB
Today
 
995486
Good Morning America
 
984661
CBS This Morning
 
835435
NFL Football
 
658048
NBC Nightly News With Lester Holt
 
570676
Other values (2199)
12453711 

Length

Max length88
Median length17
Mean length18.57859584
Min length2

Characters and Unicode

Total characters306509990
Distinct characters85
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLive with Kelly and Ryan
2nd row60 Minutes
3rd row60 Minutes
4th rowCBS This Morning
5th rowUnlocking Christmas

Common Values

ValueCountFrequency (%)
Today995486
 
5.1%
Good Morning America984661
 
5.0%
CBS This Morning835435
 
4.3%
NFL Football658048
 
3.4%
NBC Nightly News With Lester Holt570676
 
2.9%
The Price Is Right515097
 
2.6%
ABC World News Tonight With David Muir439525
 
2.2%
Wheel of Fortune305716
 
1.6%
The Young and the Restless211680
 
1.1%
The Bachelor209444
 
1.1%
Other values (2194)10772249
55.0%
(Missing)3089626
 
15.8%

Length

2021-08-26T22:54:34.106189image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the3485167
 
6.4%
with2461555
 
4.5%
news2401998
 
4.4%
morning2385880
 
4.4%
today1693126
 
3.1%
cbs1441864
 
2.6%
america1136279
 
2.1%
good1123404
 
2.1%
this1044212
 
1.9%
nfl737424
 
1.3%
Other values (2282)36818171
67.3%

Most occurring characters

ValueCountFrequency (%)
38231063
 
12.5%
e24698065
 
8.1%
o19684643
 
6.4%
i18708086
 
6.1%
a15401742
 
5.0%
n15313433
 
5.0%
t14606646
 
4.8%
r14284158
 
4.7%
h11948706
 
3.9%
s11493379
 
3.7%
Other values (75)122140069
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter200637734
65.5%
Uppercase Letter60696879
 
19.8%
Space Separator38231063
 
12.5%
Decimal Number3742372
 
1.2%
Other Punctuation3001456
 
1.0%
Dash Punctuation171276
 
0.1%
Open Punctuation14163
 
< 0.1%
Close Punctuation14163
 
< 0.1%
Math Symbol884
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e24698065
12.3%
o19684643
9.8%
i18708086
9.3%
a15401742
 
7.7%
n15313433
 
7.6%
t14606646
 
7.3%
r14284158
 
7.1%
h11948706
 
6.0%
s11493379
 
5.7%
l10306676
 
5.1%
Other values (22)44192200
22.0%
Uppercase Letter
ValueCountFrequency (%)
T6893639
11.4%
N5980219
 
9.9%
M4955219
 
8.2%
C4669336
 
7.7%
W4590591
 
7.6%
B4551627
 
7.5%
S3800548
 
6.3%
F3662406
 
6.0%
A3207819
 
5.3%
L2691773
 
4.4%
Other values (17)15693702
25.9%
Other Punctuation
ValueCountFrequency (%)
:1075574
35.8%
'683710
22.8%
.575625
19.2%
&268306
 
8.9%
,187110
 
6.2%
!171568
 
5.7%
¡18617
 
0.6%
/12108
 
0.4%
?8335
 
0.3%
#483
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0882808
23.6%
3674712
18.0%
1462259
12.4%
6454364
12.1%
5362389
9.7%
4310966
 
8.3%
2299622
 
8.0%
8114963
 
3.1%
7108414
 
2.9%
971875
 
1.9%
Space Separator
ValueCountFrequency (%)
38231063
100.0%
Dash Punctuation
ValueCountFrequency (%)
-171276
100.0%
Math Symbol
ValueCountFrequency (%)
+884
100.0%
Open Punctuation
ValueCountFrequency (%)
(14163
100.0%
Close Punctuation
ValueCountFrequency (%)
)14163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin261334613
85.3%
Common45175377
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e24698065
 
9.5%
o19684643
 
7.5%
i18708086
 
7.2%
a15401742
 
5.9%
n15313433
 
5.9%
t14606646
 
5.6%
r14284158
 
5.5%
h11948706
 
4.6%
s11493379
 
4.4%
l10306676
 
3.9%
Other values (49)104889079
40.1%
Common
ValueCountFrequency (%)
38231063
84.6%
:1075574
 
2.4%
0882808
 
2.0%
'683710
 
1.5%
3674712
 
1.5%
.575625
 
1.3%
1462259
 
1.0%
6454364
 
1.0%
5362389
 
0.8%
4310966
 
0.7%
Other values (16)1461907
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII306430443
> 99.9%
Latin 1 Sup79547
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38231063
 
12.5%
e24698065
 
8.1%
o19684643
 
6.4%
i18708086
 
6.1%
a15401742
 
5.0%
n15313433
 
5.0%
t14606646
 
4.8%
r14284158
 
4.7%
h11948706
 
3.9%
s11493379
 
3.8%
Other values (67)122060522
39.8%
Latin 1 Sup
ValueCountFrequency (%)
ó22935
28.8%
é21837
27.5%
¡18617
23.4%
í14939
18.8%
á644
 
0.8%
ñ437
 
0.5%
Á122
 
0.2%
ú16
 
< 0.1%
Distinct3207
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:00:00
Maximum2021-03-22 00:00:00
2021-08-26T22:54:34.314570image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:34.509705image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

session_duration_seconds
Real number (ℝ≥0)

HIGH CORRELATION

Distinct17662
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2761.41633
Minimum1
Maximum28800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:34.715239image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63
Q11376
median2430
Q33600
95-th percentile7200
Maximum28800
Range28799
Interquartile range (IQR)2224

Descriptive statistics

Standard deviation2076.39977
Coefficient of variation (CV)0.7519328933
Kurtosis4.407985176
Mean2761.41633
Median Absolute Deviation (MAD)1170
Skewness1.448622205
Sum5.408963724 × 1010
Variance4311436.006
MonotonicityNot monotonic
2021-08-26T22:54:34.907302image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36002277101
 
11.6%
1800956911
 
4.9%
7200720136
 
3.7%
3599347381
 
1.8%
1799139103
 
0.7%
540062270
 
0.3%
359858515
 
0.3%
719948045
 
0.2%
358644803
 
0.2%
358744501
 
0.2%
Other values (17652)14888877
76.0%
ValueCountFrequency (%)
129718
0.2%
234741
0.2%
321504
0.1%
415053
0.1%
529301
0.1%
630294
0.2%
728972
0.1%
824633
0.1%
923361
0.1%
1022329
0.1%
ValueCountFrequency (%)
28800143
< 0.1%
28799227
< 0.1%
2879842
 
< 0.1%
2879714
 
< 0.1%
287952
 
< 0.1%
287943
 
< 0.1%
287922
 
< 0.1%
287912
 
< 0.1%
287891
 
< 0.1%
287881
 
< 0.1%
Distinct2567463
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:00:00
Maximum2021-03-22 00:18:35
2021-08-26T22:54:35.113549image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:35.308459image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1996336
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:20:41
Maximum2021-03-22 01:00:00
2021-08-26T22:54:35.516934image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:35.712035image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3478
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 00:00:00
Maximum2021-03-21 23:30:00
2021-08-26T22:54:35.919990image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:36.115082image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3578
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-14 01:00:00
Maximum2021-03-22 01:00:00
2021-08-26T22:54:36.322556image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:36.517300image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

program_duration_seconds
Real number (ℝ≥0)

HIGH CORRELATION

Distinct118
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4784.301385
Minimum600
Maximum28800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:36.722731image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum600
5-th percentile1800
Q13600
median3600
Q37200
95-th percentile10800
Maximum28800
Range28200
Interquartile range (IQR)3600

Descriptive statistics

Standard deviation2804.009865
Coefficient of variation (CV)0.5860855409
Kurtosis4.790304991
Mean4784.301385
Median Absolute Deviation (MAD)1500
Skewness1.66782386
Sum9.371318754 × 1010
Variance7862471.325
MonotonicityNot monotonic
2021-08-26T22:54:36.915044image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36009245843
47.2%
72004293838
21.9%
18003266695
 
16.7%
12600524797
 
2.7%
5400347652
 
1.8%
10800340649
 
1.7%
3660191131
 
1.0%
7260186941
 
1.0%
9000164990
 
0.8%
14400151459
 
0.8%
Other values (108)873648
 
4.5%
ValueCountFrequency (%)
600215
 
< 0.1%
900918
 
< 0.1%
108033
 
< 0.1%
11409
 
< 0.1%
120057
 
< 0.1%
1380467
 
< 0.1%
14405037
< 0.1%
15006768
< 0.1%
1560586
 
< 0.1%
1620273
 
< 0.1%
ValueCountFrequency (%)
288009961
 
0.1%
252001808
 
< 0.1%
2160012283
 
0.1%
180003801
 
< 0.1%
162003260
 
< 0.1%
1578012
 
< 0.1%
14400151459
0.8%
142801
 
< 0.1%
1410012908
 
0.1%
1398062
 
< 0.1%

series_name
Categorical

HIGH CARDINALITY

Distinct2280
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 GiB
Today
 
995486
Good Morning America
 
984661
CBS This Morning
 
835435
NFL Football
 
658048
The Price Is Right
 
629590
Other values (2275)
15484423 

Length

Max length88
Median length17
Mean length18.57564511
Min length2

Characters and Unicode

Total characters363853105
Distinct characters86
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowLive with Kelly and Ryan
2nd row60 Minutes
3rd row60 Minutes
4th rowCBS This Morning
5th rowUnlocking Christmas

Common Values

ValueCountFrequency (%)
Today995486
 
5.1%
Good Morning America984661
 
5.0%
CBS This Morning835435
 
4.3%
NFL Football658048
 
3.4%
The Price Is Right629590
 
3.2%
NBC Nightly News With Lester Holt570676
 
2.9%
ABC World News Tonight With David Muir439525
 
2.2%
The View438855
 
2.2%
The Bachelor376265
 
1.9%
GMA3: What You Need to Know334310
 
1.7%
Other values (2270)13324792
68.0%

Length

2021-08-26T22:54:37.352610image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the4930148
 
7.6%
with2852281
 
4.4%
news2464772
 
3.8%
morning2415871
 
3.7%
today1693126
 
2.6%
cbs1508488
 
2.3%
america1142936
 
1.8%
good1123404
 
1.7%
this1044212
 
1.6%
and827932
 
1.3%
Other values (2395)45135661
69.3%

Most occurring characters

ValueCountFrequency (%)
45551188
 
12.5%
e31193746
 
8.6%
o22640630
 
6.2%
i21625217
 
5.9%
a18639414
 
5.1%
n17648356
 
4.9%
t17348424
 
4.8%
r16750893
 
4.6%
h15137779
 
4.2%
s13452973
 
3.7%
Other values (76)143864485
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter238757393
65.6%
Uppercase Letter71164856
 
19.6%
Space Separator45551188
 
12.5%
Decimal Number4388224
 
1.2%
Other Punctuation3723667
 
1.0%
Dash Punctuation179485
 
< 0.1%
Other Symbol58243
 
< 0.1%
Open Punctuation14163
 
< 0.1%
Close Punctuation14163
 
< 0.1%
Math Symbol1723
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e31193746
13.1%
o22640630
9.5%
i21625217
9.1%
a18639414
 
7.8%
n17648356
 
7.4%
t17348424
 
7.3%
r16750893
 
7.0%
h15137779
 
6.3%
s13452973
 
5.6%
l12753670
 
5.3%
Other values (22)51566291
21.6%
Uppercase Letter
ValueCountFrequency (%)
T8415710
11.8%
N6457566
 
9.1%
M5646786
 
7.9%
W5410778
 
7.6%
B5335092
 
7.5%
C5264265
 
7.4%
S4341494
 
6.1%
F4030206
 
5.7%
A3830564
 
5.4%
L2954771
 
4.2%
Other values (17)19477624
27.4%
Other Punctuation
ValueCountFrequency (%)
:1410428
37.9%
'869698
23.4%
.737844
19.8%
&292251
 
7.8%
,191569
 
5.1%
!183628
 
4.9%
/16296
 
0.4%
¡12060
 
0.3%
?9390
 
0.3%
#483
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
01037924
23.7%
3911893
20.8%
6597356
13.6%
1530175
12.1%
5362518
 
8.3%
2337593
 
7.7%
4313435
 
7.1%
8118999
 
2.7%
7108414
 
2.5%
969917
 
1.6%
Space Separator
ValueCountFrequency (%)
45551188
100.0%
Dash Punctuation
ValueCountFrequency (%)
-179485
100.0%
Math Symbol
ValueCountFrequency (%)
+1723
100.0%
Other Symbol
ValueCountFrequency (%)
58243
100.0%
Open Punctuation
ValueCountFrequency (%)
(14163
100.0%
Close Punctuation
ValueCountFrequency (%)
)14163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin309922249
85.2%
Common53930856
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e31193746
 
10.1%
o22640630
 
7.3%
i21625217
 
7.0%
a18639414
 
6.0%
n17648356
 
5.7%
t17348424
 
5.6%
r16750893
 
5.4%
h15137779
 
4.9%
s13452973
 
4.3%
l12753670
 
4.1%
Other values (49)122731147
39.6%
Common
ValueCountFrequency (%)
45551188
84.5%
:1410428
 
2.6%
01037924
 
1.9%
3911893
 
1.7%
'869698
 
1.6%
.737844
 
1.4%
6597356
 
1.1%
1530175
 
1.0%
5362518
 
0.7%
2337593
 
0.6%
Other values (17)1584239
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII363705822
> 99.9%
Latin 1 Sup89040
 
< 0.1%
Specials58243
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45551188
 
12.5%
e31193746
 
8.6%
o22640630
 
6.2%
i21625217
 
5.9%
a18639414
 
5.1%
n17648356
 
4.9%
t17348424
 
4.8%
r16750893
 
4.6%
h15137779
 
4.2%
s13452973
 
3.7%
Other values (67)143717202
39.5%
Specials
ValueCountFrequency (%)
58243
100.0%
Latin 1 Sup
ValueCountFrequency (%)
í26272
29.5%
ó24650
27.7%
é15190
17.1%
¡12060
13.5%
ñ4020
 
4.5%
ú3530
 
4.0%
á3167
 
3.6%
Á151
 
0.2%

episode_title
Categorical

HIGH CARDINALITY
MISSING

Distinct2626
Distinct (%)< 0.1%
Missing6763657
Missing (%)34.5%
Memory size1.0 GiB
6350029 
Chicago Bears at New Orleans Saints
 
359053
The Equalizer
 
143541
America's Game
 
89179
Indianapolis Colts at Buffalo Bills
 
86058
Other values (2621)
5796126 

Length

Max length140
Median length5
Mean length11.53935953
Min length0

Characters and Unicode

Total characters147980585
Distinct characters92
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLive's Family Cooking Week
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
6350029
32.4%
Chicago Bears at New Orleans Saints359053
 
1.8%
The Equalizer143541
 
0.7%
America's Game89179
 
0.5%
Indianapolis Colts at Buffalo Bills86058
 
0.4%
Baltimore Ravens at Tennessee Titans83705
 
0.4%
Cleveland Browns at Kansas City Chiefs74439
 
0.4%
Wheel Around the World60898
 
0.3%
Rail Tour58790
 
0.3%
Great Outdoors56794
 
0.3%
Other values (2616)5461500
27.9%
(Missing)6763657
34.5%

Length

2021-08-26T22:54:37.817480image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the1566853
 
6.1%
at859169
 
3.3%
455481
 
1.8%
and430605
 
1.7%
new415110
 
1.6%
of398984
 
1.5%
a371606
 
1.4%
chicago361889
 
1.4%
bears360197
 
1.4%
saints359756
 
1.4%
Other values (4394)20310488
78.4%

Most occurring characters

ValueCountFrequency (%)
19416181
 
13.1%
e14173802
 
9.6%
a11270680
 
7.6%
n8361953
 
5.7%
o8108137
 
5.5%
i7756122
 
5.2%
t7733104
 
5.2%
r7129470
 
4.8%
s7087689
 
4.8%
l5563024
 
3.8%
Other values (82)51380423
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter102920686
69.6%
Uppercase Letter21782896
 
14.7%
Space Separator19416181
 
13.1%
Other Punctuation2039621
 
1.4%
Decimal Number971949
 
0.7%
Math Symbol381289
 
0.3%
Dash Punctuation242539
 
0.2%
Open Punctuation103604
 
0.1%
Close Punctuation103604
 
0.1%
Other Symbol11806
 
< 0.1%
Other values (2)6410
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e14173802
13.8%
a11270680
11.0%
n8361953
 
8.1%
o8108137
 
7.9%
i7756122
 
7.5%
t7733104
 
7.5%
r7129470
 
6.9%
s7087689
 
6.9%
l5563024
 
5.4%
h4277664
 
4.2%
Other values (23)21459041
20.9%
Uppercase Letter
ValueCountFrequency (%)
T2147082
 
9.9%
B1998254
 
9.2%
S1749402
 
8.0%
C1685683
 
7.7%
A1265881
 
5.8%
W1130347
 
5.2%
M1096630
 
5.0%
D1089135
 
5.0%
O948108
 
4.4%
P931523
 
4.3%
Other values (18)7740851
35.5%
Other Punctuation
ValueCountFrequency (%)
'563083
27.6%
,557362
27.3%
.297943
14.6%
:201697
 
9.9%
?199184
 
9.8%
;120305
 
5.9%
!48092
 
2.4%
&29522
 
1.4%
"16262
 
0.8%
¿2622
 
0.1%
Other values (3)3549
 
0.2%
Decimal Number
ValueCountFrequency (%)
0215148
22.1%
2181761
18.7%
1146201
15.0%
4143635
14.8%
5115726
11.9%
349429
 
5.1%
947693
 
4.9%
641279
 
4.2%
722614
 
2.3%
88463
 
0.9%
Space Separator
ValueCountFrequency (%)
19416181
100.0%
Dash Punctuation
ValueCountFrequency (%)
-242539
100.0%
Other Symbol
ValueCountFrequency (%)
11806
100.0%
Currency Symbol
ValueCountFrequency (%)
$2032
100.0%
Math Symbol
ValueCountFrequency (%)
+381289
100.0%
Modifier Symbol
ValueCountFrequency (%)
`4378
100.0%
Open Punctuation
ValueCountFrequency (%)
(103604
100.0%
Close Punctuation
ValueCountFrequency (%)
)103604
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin124703582
84.3%
Common23277003
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e14173802
 
11.4%
a11270680
 
9.0%
n8361953
 
6.7%
o8108137
 
6.5%
i7756122
 
6.2%
t7733104
 
6.2%
r7129470
 
5.7%
s7087689
 
5.7%
l5563024
 
4.5%
h4277664
 
3.4%
Other values (51)43241937
34.7%
Common
ValueCountFrequency (%)
19416181
83.4%
'563083
 
2.4%
,557362
 
2.4%
+381289
 
1.6%
.297943
 
1.3%
-242539
 
1.0%
0215148
 
0.9%
:201697
 
0.9%
?199184
 
0.9%
2181761
 
0.8%
Other values (21)1020816
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII147910685
> 99.9%
Latin 1 Sup58094
 
< 0.1%
Specials11806
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19416181
 
13.1%
e14173802
 
9.6%
a11270680
 
7.6%
n8361953
 
5.7%
o8108137
 
5.5%
i7756122
 
5.2%
t7733104
 
5.2%
r7129470
 
4.8%
s7087689
 
4.8%
l5563024
 
3.8%
Other values (71)51310523
34.7%
Specials
ValueCountFrequency (%)
11806
100.0%
Latin 1 Sup
ValueCountFrequency (%)
Å15082
26.0%
ó10982
18.9%
á8605
14.8%
é7940
13.7%
í6881
11.8%
ñ4304
 
7.4%
¿2622
 
4.5%
ú1464
 
2.5%
Ú188
 
0.3%
ü26
 
< 0.1%

season_number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct50
Distinct (%)< 0.1%
Missing3089626
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean805.091865
Minimum0
Maximum2021
Zeros3544177
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:38.039060image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median25
Q32021
95-th percentile2021
Maximum2021
Range2021
Interquartile range (IQR)2020

Descriptive statistics

Standard deviation982.4743657
Coefficient of variation (CV)1.220325789
Kurtosis-1.815126117
Mean805.091865
Median Absolute Deviation (MAD)25
Skewness0.429016938
Sum1.328241928 × 1010
Variance965255.8793
MonotonicityNot monotonic
2021-08-26T22:54:38.238436image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20215943460
30.3%
03544177
18.1%
1871038
 
4.4%
2625031
 
3.2%
2020570360
 
2.9%
49515097
 
2.6%
3480214
 
2.5%
5388467
 
2.0%
4332332
 
1.7%
38288827
 
1.5%
Other values (40)2939014
15.0%
(Missing)3089626
15.8%
ValueCountFrequency (%)
03544177
18.1%
1871038
 
4.4%
2625031
 
3.2%
3480214
 
2.5%
4332332
 
1.7%
5388467
 
2.0%
6224710
 
1.1%
7122995
 
0.6%
8226133
 
1.2%
9170722
 
0.9%
ValueCountFrequency (%)
20215943460
30.3%
2020570360
 
2.9%
2017479
 
< 0.1%
20161016
 
< 0.1%
2015669
 
< 0.1%
2010154
 
< 0.1%
1972361
 
< 0.1%
1915365
 
< 0.1%
1791187
 
< 0.1%
16114300
 
0.1%

episode_number
Real number (ℝ≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct216
Distinct (%)< 0.1%
Missing3089626
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean31.80780533
Minimum0
Maximum1059
Zeros3632098
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:38.450881image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median11
Q339
95-th percentile108
Maximum1059
Range1059
Interquartile range (IQR)37

Descriptive statistics

Standard deviation58.94310129
Coefficient of variation (CV)1.8531018
Kurtosis51.18598924
Mean31.80780533
Median Absolute Deviation (MAD)11
Skewness5.347993898
Sum524765713
Variance3474.28919
MonotonicityNot monotonic
2021-08-26T22:54:38.652034image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03632098
18.5%
6644135
 
3.3%
3569443
 
2.9%
7527024
 
2.7%
2499983
 
2.6%
4455878
 
2.3%
1439066
 
2.2%
8402038
 
2.1%
5373497
 
1.9%
10362769
 
1.9%
Other values (206)8592086
43.9%
(Missing)3089626
 
15.8%
ValueCountFrequency (%)
03632098
18.5%
1439066
 
2.2%
2499983
 
2.6%
3569443
 
2.9%
4455878
 
2.3%
5373497
 
1.9%
6644135
 
3.3%
7527024
 
2.7%
8402038
 
2.1%
9318196
 
1.6%
ValueCountFrequency (%)
10592623
 
< 0.1%
9712669
 
< 0.1%
9133023
 
< 0.1%
7081499
 
< 0.1%
7062716
 
< 0.1%
7023553
 
< 0.1%
64365
 
< 0.1%
4134406
 
< 0.1%
40231666
0.2%
3614566
 
< 0.1%

network
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct79
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 GiB
CBS
4864314 
ABC
4402122 
NBC
3524155 
FNC
844362 
MSNBC
786768 
Other values (74)
5165922 

Length

Max length7
Median length3
Mean length3.240141093
Min length1

Characters and Unicode

Total characters63466727
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowABC
2nd rowCBS
3rd rowCBS
4th rowCBS
5th rowHMM

Common Values

ValueCountFrequency (%)
CBS4864314
24.8%
ABC4402122
22.5%
NBC3524155
18.0%
FNC844362
 
4.3%
MSNBC786768
 
4.0%
CNN523449
 
2.7%
HALL441158
 
2.3%
HMM304972
 
1.6%
TVLAND285180
 
1.5%
ESPN274399
 
1.4%
Other values (69)3336764
17.0%

Length

2021-08-26T22:54:39.075105image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cbs4864314
24.8%
abc4402122
22.5%
nbc3524155
18.0%
fnc844362
 
4.3%
msnbc786768
 
4.0%
cnn523449
 
2.7%
hall441158
 
2.3%
hmm304972
 
1.6%
tvland285180
 
1.5%
espn274399
 
1.4%
Other values (69)3336764
17.0%

Most occurring characters

ValueCountFrequency (%)
C15600469
24.6%
B13959239
22.0%
N8008725
12.6%
S6842377
10.8%
A5686632
 
9.0%
L1590474
 
2.5%
F1542266
 
2.4%
M1512899
 
2.4%
H1251220
 
2.0%
T1145375
 
1.8%
Other values (15)6327051
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter63432176
99.9%
Decimal Number34551
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C15600469
24.6%
B13959239
22.0%
N8008725
12.6%
S6842377
10.8%
A5686632
 
9.0%
L1590474
 
2.5%
F1542266
 
2.4%
M1512899
 
2.4%
H1251220
 
2.0%
T1145375
 
1.8%
Other values (13)6292500
9.9%
Decimal Number
ValueCountFrequency (%)
234288
99.2%
1263
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin63432176
99.9%
Common34551
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C15600469
24.6%
B13959239
22.0%
N8008725
12.6%
S6842377
10.8%
A5686632
 
9.0%
L1590474
 
2.5%
F1542266
 
2.4%
M1512899
 
2.4%
H1251220
 
2.0%
T1145375
 
1.8%
Other values (13)6292500
9.9%
Common
ValueCountFrequency (%)
234288
99.2%
1263
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII63466727
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C15600469
24.6%
B13959239
22.0%
N8008725
12.6%
S6842377
10.8%
A5686632
 
9.0%
L1590474
 
2.5%
F1542266
 
2.4%
M1512899
 
2.4%
H1251220
 
2.0%
T1145375
 
1.8%
Other values (15)6327051
10.0%

callsign
Categorical

HIGH CARDINALITY

Distinct1274
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 GiB
FNC
 
844362
MSNBC
 
786768
CNN
 
523449
HALL
 
441158
WPVIDT
 
362254
Other values (1269)
16629652 

Length

Max length7
Median length6
Mean length5.210251432
Min length1

Characters and Unicode

Total characters102056545
Distinct characters31
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowWKOWDT
2nd rowWISCDT
3rd rowWISCDT
4th rowWISCDT
5th rowHMM

Common Values

ValueCountFrequency (%)
FNC844362
 
4.3%
MSNBC786768
 
4.0%
CNN523449
 
2.7%
HALL441158
 
2.3%
WPVIDT362254
 
1.8%
HMM304972
 
1.6%
TVLAND285180
 
1.5%
WABCDT283264
 
1.4%
ESPN274399
 
1.4%
KABC264586
 
1.4%
Other values (1264)15217251
77.7%

Length

2021-08-26T22:54:39.488053image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fnc844362
 
4.3%
msnbc786768
 
4.0%
cnn523449
 
2.7%
hall441158
 
2.3%
wpvidt362254
 
1.8%
hmm304972
 
1.6%
tvland285180
 
1.5%
wabcdt283264
 
1.4%
espn274399
 
1.4%
kabc264586
 
1.4%
Other values (1264)15217251
77.7%

Most occurring characters

ValueCountFrequency (%)
T17501705
17.1%
D14570549
14.3%
W9290552
 
9.1%
C6216847
 
6.1%
K6022124
 
5.9%
N5909896
 
5.8%
A4527508
 
4.4%
S4318723
 
4.2%
B4150486
 
4.1%
V3274211
 
3.2%
Other values (21)26273944
25.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter101943614
99.9%
Decimal Number112931
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T17501705
17.2%
D14570549
14.3%
W9290552
 
9.1%
C6216847
 
6.1%
K6022124
 
5.9%
N5909896
 
5.8%
A4527508
 
4.4%
S4318723
 
4.2%
B4150486
 
4.1%
V3274211
 
3.2%
Other values (16)26161013
25.7%
Decimal Number
ValueCountFrequency (%)
2106422
94.2%
34772
 
4.2%
1959
 
0.8%
5696
 
0.6%
482
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin101943614
99.9%
Common112931
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T17501705
17.2%
D14570549
14.3%
W9290552
 
9.1%
C6216847
 
6.1%
K6022124
 
5.9%
N5909896
 
5.8%
A4527508
 
4.4%
S4318723
 
4.2%
B4150486
 
4.1%
V3274211
 
3.2%
Other values (16)26161013
25.7%
Common
ValueCountFrequency (%)
2106422
94.2%
34772
 
4.2%
1959
 
0.8%
5696
 
0.6%
482
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII102056545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T17501705
17.1%
D14570549
14.3%
W9290552
 
9.1%
C6216847
 
6.1%
K6022124
 
5.9%
N5909896
 
5.8%
A4527508
 
4.4%
S4318723
 
4.2%
B4150486
 
4.1%
V3274211
 
3.2%
Other values (21)26273944
25.7%

media_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct22
Distinct (%)< 0.1%
Missing1307
Missing (%)< 0.1%
Memory size1.3 GiB
ViacomCBS
5217338 
NBCUniversal
4942880 
Disney Media Networks
4871038 
Fox
1163081 
Discovery
874298 
Other values (17)
2517701 

Length

Max length45
Median length12
Mean length13.45425178
Min length3

Characters and Unicode

Total characters263519496
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDisney Media Networks
2nd rowViacomCBS
3rd rowViacomCBS
4th rowViacomCBS
5th rowCrownMedia Family Network

Common Values

ValueCountFrequency (%)
ViacomCBS5217338
26.6%
NBCUniversal4942880
25.2%
Disney Media Networks4871038
24.9%
Fox1163081
 
5.9%
Discovery874298
 
4.5%
WarnerMedia803536
 
4.1%
CrownMedia Family Network746130
 
3.8%
A+E Networks252531
 
1.3%
Univision Communications175185
 
0.9%
Sony Pictures137178
 
0.7%
Other values (12)403141
 
2.1%

Length

2021-08-26T22:54:39.846884image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
viacomcbs5258758
16.4%
networks5169218
16.2%
media5059493
15.8%
nbcuniversal4942880
15.4%
disney4871038
15.2%
fox1163081
 
3.6%
discovery874298
 
2.7%
warnermedia845060
 
2.6%
network746130
 
2.3%
family746130
 
2.3%
Other values (28)2328423
7.3%

Most occurring characters

ValueCountFrequency (%)
i24771097
 
9.4%
e24524434
 
9.3%
a18875695
 
7.2%
s16683025
 
6.3%
o14891004
 
5.7%
r14766910
 
5.6%
n12740885
 
4.8%
12418173
 
4.7%
C11172427
 
4.2%
N10934129
 
4.1%
Other values (36)101741717
38.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter186104639
70.6%
Uppercase Letter64547664
 
24.5%
Space Separator12418173
 
4.7%
Math Symbol252531
 
0.1%
Other Punctuation196489
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i24771097
13.3%
e24524434
13.2%
a18875695
10.1%
s16683025
9.0%
o14891004
 
8.0%
r14766910
 
7.9%
n12740885
 
6.8%
d6687779
 
3.6%
w6661478
 
3.6%
y6628644
 
3.6%
Other values (12)38873688
20.9%
Uppercase Letter
ValueCountFrequency (%)
C11172427
17.3%
N10934129
16.9%
B10201742
15.8%
M6807269
10.5%
D5745336
8.9%
S5395936
8.4%
V5258758
8.1%
U5130589
7.9%
F1909438
 
3.0%
W848602
 
1.3%
Other values (9)1143438
 
1.8%
Other Punctuation
ValueCountFrequency (%)
,79395
40.4%
.75570
38.5%
&41524
21.1%
Space Separator
ValueCountFrequency (%)
12418173
100.0%
Math Symbol
ValueCountFrequency (%)
+252531
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin250652303
95.1%
Common12867193
 
4.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i24771097
 
9.9%
e24524434
 
9.8%
a18875695
 
7.5%
s16683025
 
6.7%
o14891004
 
5.9%
r14766910
 
5.9%
n12740885
 
5.1%
C11172427
 
4.5%
N10934129
 
4.4%
B10201742
 
4.1%
Other values (31)91090955
36.3%
Common
ValueCountFrequency (%)
12418173
96.5%
+252531
 
2.0%
,79395
 
0.6%
.75570
 
0.6%
&41524
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII263519496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i24771097
 
9.4%
e24524434
 
9.3%
a18875695
 
7.2%
s16683025
 
6.3%
o14891004
 
5.7%
r14766910
 
5.6%
n12740885
 
4.8%
12418173
 
4.7%
C11172427
 
4.2%
N10934129
 
4.1%
Other values (36)101741717
38.6%

market_name
Categorical

HIGH CARDINALITY

Distinct210
Distinct (%)< 0.1%
Missing155931
Missing (%)0.8%
Memory size1.4 GiB
New York NY
 
972744
Los Angeles CA
 
911697
Philadelphia PA
 
889464
Tampa-St.Petersburg-Sarasota FL
 
636715
Dallas-Ft.Worth TX
 
612316
Other values (205)
15408776 

Length

Max length50
Median length17
Mean length19.32345241
Min length7

Characters and Unicode

Total characters375487762
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMadison WI
2nd rowMadison WI
3rd rowMadison WI
4th rowMadison WI
5th rowDavenport IA-Rock Island-Moline IL

Common Values

ValueCountFrequency (%)
New York NY972744
 
5.0%
Los Angeles CA911697
 
4.7%
Philadelphia PA889464
 
4.5%
Tampa-St.Petersburg-Sarasota FL636715
 
3.3%
Dallas-Ft.Worth TX612316
 
3.1%
Chicago IL560245
 
2.9%
Pittsburgh PA469644
 
2.4%
Boston MA-Manchester NH359332
 
1.8%
Wilkes Barre-Scranton PA338919
 
1.7%
Washington DC-Hagerstown MD327235
 
1.7%
Other values (200)13353401
68.2%

Length

2021-08-26T22:54:40.263368image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pa2009674
 
4.0%
tx1792871
 
3.6%
ca1624272
 
3.2%
fl1526065
 
3.0%
ny1269825
 
2.5%
il1066093
 
2.1%
new1059918
 
2.1%
york972744
 
1.9%
angeles911697
 
1.8%
los911697
 
1.8%
Other values (330)36989320
73.8%

Most occurring characters

ValueCountFrequency (%)
30702464
 
8.2%
a28410452
 
7.6%
e25964054
 
6.9%
o22309364
 
5.9%
t19113629
 
5.1%
n19011524
 
5.1%
l17220613
 
4.6%
r16674771
 
4.4%
i15883602
 
4.2%
s15590032
 
4.2%
Other values (44)164607257
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter240524898
64.1%
Uppercase Letter87400374
 
23.3%
Space Separator30702464
 
8.2%
Dash Punctuation14527193
 
3.9%
Other Punctuation2332833
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A10793241
 
12.3%
C7272601
 
8.3%
P6305909
 
7.2%
L5992947
 
6.9%
N5970770
 
6.8%
S5926216
 
6.8%
M5752028
 
6.6%
T4359251
 
5.0%
D4055092
 
4.6%
F3958746
 
4.5%
Other values (16)27013573
30.9%
Lowercase Letter
ValueCountFrequency (%)
a28410452
11.8%
e25964054
10.8%
o22309364
9.3%
t19113629
 
7.9%
n19011524
 
7.9%
l17220613
 
7.2%
r16674771
 
6.9%
i15883602
 
6.6%
s15590032
 
6.5%
h8124542
 
3.4%
Other values (15)52222315
21.7%
Space Separator
ValueCountFrequency (%)
30702464
100.0%
Dash Punctuation
ValueCountFrequency (%)
-14527193
100.0%
Other Punctuation
ValueCountFrequency (%)
.2332833
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin327925272
87.3%
Common47562490
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a28410452
 
8.7%
e25964054
 
7.9%
o22309364
 
6.8%
t19113629
 
5.8%
n19011524
 
5.8%
l17220613
 
5.3%
r16674771
 
5.1%
i15883602
 
4.8%
s15590032
 
4.8%
A10793241
 
3.3%
Other values (41)136953990
41.8%
Common
ValueCountFrequency (%)
30702464
64.6%
-14527193
30.5%
.2332833
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII375487762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30702464
 
8.2%
a28410452
 
7.6%
e25964054
 
6.9%
o22309364
 
5.9%
t19113629
 
5.1%
n19011524
 
5.1%
l17220613
 
4.6%
r16674771
 
4.4%
i15883602
 
4.2%
s15590032
 
4.2%
Other values (44)164607257
43.8%

timeshift_seconds
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct378563
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10276.06117
Minimum0
Maximum775446
Zeros13628575
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:40.462942image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile40192
Maximum775446
Range775446
Interquartile range (IQR)1

Descriptive statistics

Standard deviation54416.53292
Coefficient of variation (CV)5.295466035
Kurtosis65.23500301
Mean10276.06117
Median Absolute Deviation (MAD)0
Skewness7.564721294
Sum2.012838177 × 1011
Variance2961159055
MonotonicityNot monotonic
2021-08-26T22:54:40.671679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
013628575
69.6%
11983203
 
10.1%
2413121
 
2.1%
387483
 
0.4%
179550500
 
0.3%
179432327
 
0.2%
425524
 
0.1%
179619623
 
0.1%
514361
 
0.1%
179311794
 
0.1%
Other values (378553)3321132
 
17.0%
ValueCountFrequency (%)
013628575
69.6%
11983203
 
10.1%
2413121
 
2.1%
387483
 
0.4%
425524
 
0.1%
514361
 
0.1%
69136
 
< 0.1%
77055
 
< 0.1%
88007
 
< 0.1%
96983
 
< 0.1%
ValueCountFrequency (%)
7754461
< 0.1%
7754251
< 0.1%
7753341
< 0.1%
7751151
< 0.1%
7748671
< 0.1%
7748281
< 0.1%
7746341
< 0.1%
7744541
< 0.1%
7741421
< 0.1%
7740751
< 0.1%

timeshift_name
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 GiB
live
13628575 
liveplussd
5347755 
liveplus3
 
361989
liveplus7
 
230292
all
 
19032

Length

Max length10
Median length4
Mean length5.788316389
Min length3

Characters and Unicode

Total characters113379475
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlive
2nd rowlive
3rd rowlive
4th rowlive
5th rowliveplussd

Common Values

ValueCountFrequency (%)
live13628575
69.6%
liveplussd5347755
 
27.3%
liveplus3361989
 
1.8%
liveplus7230292
 
1.2%
all19032
 
0.1%

Length

2021-08-26T22:54:41.058007image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-08-26T22:54:41.180497image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
live13628575
69.6%
liveplussd5347755
 
27.3%
liveplus3361989
 
1.8%
liveplus7230292
 
1.2%
all19032
 
0.1%

Most occurring characters

ValueCountFrequency (%)
l25546711
22.5%
i19568611
17.3%
v19568611
17.3%
e19568611
17.3%
s11287791
10.0%
p5940036
 
5.2%
u5940036
 
5.2%
d5347755
 
4.7%
3361989
 
0.3%
7230292
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112787194
99.5%
Decimal Number592281
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l25546711
22.7%
i19568611
17.4%
v19568611
17.4%
e19568611
17.4%
s11287791
10.0%
p5940036
 
5.3%
u5940036
 
5.3%
d5347755
 
4.7%
a19032
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3361989
61.1%
7230292
38.9%

Most occurring scripts

ValueCountFrequency (%)
Latin112787194
99.5%
Common592281
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l25546711
22.7%
i19568611
17.4%
v19568611
17.4%
e19568611
17.4%
s11287791
10.0%
p5940036
 
5.3%
u5940036
 
5.3%
d5347755
 
4.7%
a19032
 
< 0.1%
Common
ValueCountFrequency (%)
3361989
61.1%
7230292
38.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII113379475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l25546711
22.5%
i19568611
17.3%
v19568611
17.3%
e19568611
17.3%
s11287791
10.0%
p5940036
 
5.2%
u5940036
 
5.2%
d5347755
 
4.7%
3361989
 
0.3%
7230292
 
0.2%

east_coast_offset_seconds
Real number (ℝ)

ZEROS

Distinct76
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-959.806914
Minimum-61560
Maximum36000
Zeros16423654
Zeros (%)83.8%
Negative2954226
Negative (%)15.1%
Memory size149.4 MiB
2021-08-26T22:54:41.338747image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum-61560
5-th percentile-7200
Q10
median0
Q30
95-th percentile0
Maximum36000
Range97560
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2861.018559
Coefficient of variation (CV)-2.980827204
Kurtosis22.6440384
Mean-959.806914
Median Absolute Deviation (MAD)0
Skewness-3.741991089
Sum-1.880035518 × 1010
Variance8185427.197
MonotonicityNot monotonic
2021-08-26T22:54:41.551402image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
016423654
83.8%
-36001520890
 
7.8%
-10800842596
 
4.3%
-7200437266
 
2.2%
1800136889
 
0.7%
-180045691
 
0.2%
720037919
 
0.2%
360034899
 
0.2%
-1440030789
 
0.2%
-540019587
 
0.1%
Other values (66)57463
 
0.3%
ValueCountFrequency (%)
-615602
 
< 0.1%
-6000012
 
< 0.1%
-594002
 
< 0.1%
-5772020
 
< 0.1%
-4722028
 
< 0.1%
-4542096
 
< 0.1%
-45360896
< 0.1%
-3996071
 
< 0.1%
-3960057
 
< 0.1%
-381601003
< 0.1%
ValueCountFrequency (%)
3600011
 
< 0.1%
3240045
 
< 0.1%
720037919
 
0.2%
360034899
 
0.2%
1800136889
 
0.7%
016423654
83.8%
-6047
 
< 0.1%
-180045691
 
0.2%
-24002486
 
< 0.1%
-36001520890
 
7.8%

full_panel_intab_weekly_weight
Real number (ℝ≥0)

MISSING

Distinct2938708
Distinct (%)15.9%
Missing1135274
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean27.45272316
Minimum1
Maximum811.523236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size149.4 MiB
2021-08-26T22:54:41.774299image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.799529122
median23.05207007
Q341.45007106
95-th percentile75.8737457
Maximum811.523236
Range810.523236
Interquartile range (IQR)38.65054194

Descriptive statistics

Standard deviation26.13403377
Coefficient of variation (CV)0.9519650789
Kurtosis4.464549806
Mean27.45272316
Median Absolute Deviation (MAD)19.26623718
Skewness1.43345578
Sum506567777.8
Variance682.987721
MonotonicityNot monotonic
2021-08-26T22:54:41.982725image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14313201
 
22.0%
25.09884225326
 
< 0.1%
40.66802436320
 
< 0.1%
8.935577927294
 
< 0.1%
6.930976876289
 
< 0.1%
72.01626038289
 
< 0.1%
127.7255278283
 
< 0.1%
20.22227751281
 
< 0.1%
27.69559947267
 
< 0.1%
65.24259306257
 
< 0.1%
Other values (2938698)14136562
72.2%
(Missing)1135274
 
5.8%
ValueCountFrequency (%)
14313201
22.0%
1.0000133133
 
< 0.1%
1.0000700033
 
< 0.1%
1.0000734342
 
< 0.1%
1.0001023423
 
< 0.1%
1.0001101991
 
< 0.1%
1.0001329864
 
< 0.1%
1.00013851610
 
< 0.1%
1.0001513421
 
< 0.1%
1.0001581715
 
< 0.1%
ValueCountFrequency (%)
811.52323623
 
< 0.1%
394.247825765
< 0.1%
376.592502326
 
< 0.1%
347.84346959
< 0.1%
318.65059742
 
< 0.1%
313.907348433
< 0.1%
311.04208456
 
< 0.1%
288.09642557
 
< 0.1%
283.558550240
< 0.1%
279.949364311
 
< 0.1%
Distinct2941195
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-13 14:00:00
Maximum2021-03-21 21:37:38
2021-08-26T22:54:42.201806image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:42.396870image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2385758
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size149.4 MiB
Minimum2020-12-13 14:59:59
Maximum2021-03-21 23:59:52
2021-08-26T22:54:42.604732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:54:42.799950image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

airing_date_utc
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size747.2 MiB

Interactions

2021-08-26T22:42:55.276005image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:42:59.158672image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:03.277206image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:07.297943image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:10.628001image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:14.137029image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:17.956120image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:21.810178image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:25.691428image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:29.681398image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:33.499944image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:37.616781image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:41.642658image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:44.947090image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:48.472168image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:52.252112image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:43:56.110010image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:00.071986image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:03.935486image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:07.855249image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:11.954013image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:15.920861image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:19.258558image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:22.755041image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:26.550738image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:30.429159image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:34.312109image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:38.281731image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:42.307708image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:46.514031image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:50.464647image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:53.781197image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:44:57.258351image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:01.093344image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:04.979415image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:08.867006image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:12.211572image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:15.603951image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:19.207304image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:22.751733image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:25.943433image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:29.362912image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:32.720098image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:36.099884image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:39.387613image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:42.794715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:46.198416image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:49.866626image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:53.386848image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:56.622574image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:45:59.973268image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:03.304607image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:06.660087image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:09.939529image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:13.676246image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:17.495067image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:21.548142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:25.514340image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:28.823123image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:32.263339image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:36.044539image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:39.868944image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:43.693994image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:47.555501image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:51.471974image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-08-26T22:46:55.572549image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/